AI_Cloud Essentials

CoreWeave

Breakthroughs stall when leaders are forced to build the future on foundations from another era. Modern AI demands new thinking, tooling and decision patterns, yet many executives feel trapped by outdated playbooks. AI Cloud Essentials clears that bottleneck. Hosted by Independent AI Value Strategist Ritu Jyoti, the show delivers practical guidance for leaders navigating trillion-parameter models, real-time adaptation and fast-moving AI ecosystems. Each episode offers clear frameworks to help teams innovate faster, scale smarter and reduce friction without jargon or recycled thinking.

Episodes

  1. FEB 24

    Future-Proof Your Enterprise AI: The Decisive Strategic Choice You Must Make Now

    AI native cloud strategy now determines who can scale AI and who stalls out. AI native cloud decisions directly impact cost control, speed to market, and competitive advantage as agentic AI moves from pilots to production. In this episode, leaders explain why the wrong AI foundation quietly becomes a business risk. In this episode of AI Cloud Essentials presented by CoreWeave, host Ritu Jyoti, Independent AI Strategist, is joined by Jean English, Chief Marketing Officer of CoreWeave, to take AI out of the infrastructure weeds and into the boardroom. They break down why general purpose cloud platforms were never designed for AI at scale and how AI native cloud architectures unlock faster innovation, better economics, and real business velocity. In this episode, you will learn how to: Tell if your current AI stack is enabling growth or slowing it down Understand the real differences between general purpose cloud and AI native cloud Move AI from prototype to production without friction Improve GPU utilization and cost predictability at scale Balance speed, security, and governance for enterprise AI Align AI infrastructure decisions with executive and board level outcomes Future proof your organization for agentic AI and next generation workloads The gap between AI leaders and laggards is widening fast. Do not risk rising costs, stalled innovation, or strategic lock in. Learn how to build an AI native foundation that protects speed, control, and competitive advantage while there is still time to lead.

    24 min
  2. FEB 10

    Migration Risk? Debunking the Myths to Get to AI-Native Cloud, Fast

    AI cloud migration no longer has to be risky, disruptive, or slow. In this episode of AI Cloud Essentials, we break down the biggest myths holding enterprises back from AI cloud migration and show why moving to an AI-native cloud is far easier and more strategic than most leaders believe. If your organization is overspending on legacy cloud infrastructure while still feeling unprepared for AI, this episode delivers a clear path forward. Host Ritu Jyoti sits down with Corey Sanders, SVP of Strategy at CoreWeave, to dismantle the fear around AI cloud migration and reframe it as replatforming for intelligence, not a risky lift-and-shift. Together, they explore why general-purpose clouds create hidden cost, operational drag, and innovation bottlenecks for AI workloads, and how an AI-native cloud enables faster experimentation, zero-downtime transitions, and real business velocity. Brought to you by CoreWeave, this conversation is built for CIOs, CTOs, and enterprise leaders who need to move decisively without breaking what already works. In this episode, you’ll learn: Why AI cloud migration is not a “big bang” data center evacuationHow AI-native clouds eliminate wasted GPU cycles and legacy cloud taxWhy incremental, parallel migration enables zero downtimeHow AI workloads shift cloud strategy from cost center to revenue driverWhy inactivity is the biggest risk enterprises face with AIHow to prioritize the right workloads to accelerate AI ROI fastDon’t risk falling behind by delaying your AI cloud migration. Learn how to move to an AI-native cloud with confidence, cut hidden costs, and unlock real AI value before competitors do.

    24 min
  3. JAN 27

    The AI Risk Blind Spot: Are General-Purpose Clouds Leaving Your Enterprise Exposed?

    AI cloud security is no longer a future concern, it is an urgent enterprise risk hiding in plain sight. In this episode of AI Cloud Essentials, brought to you by CoreWeave, we expose the AI cloud security blind spot most organizations miss and explain why traditional perimeter defenses fail modern AI workloads. If your AI strategy touches proprietary data, models, or business logic, this conversation could save you from costly exposure. In Episode 4, host Ritu Jyoti is joined by James Higgins, Chief Security Officer at CoreWeave, to unpack how AI fundamentally changes the shared responsibility model in the cloud. They explore why AI risk now lives inside the model, the prompt, and the data flows, not just the network, and why AI native infrastructure, governance, and zero trust, data centric security are quickly becoming non negotiable as regulators, attackers, and autonomous systems outpace legacy security tools. In this episode, you’ll learn: Why the shared responsibility model breaks down for AI workloads How prompt injection, data poisoning, and model drift create new security risks Why general purpose cloud security tools fail AI systems How AI native infrastructure changes the security equation The top actions enterprise leaders should take in the next 90 to 180 days Don’t risk your AI models becoming your biggest liability. Learn how to secure AI workloads properly before blind spots turn into breaches.

    19 min
  4. JAN 13

    The AIOps Black Hole: Escaping the Complexity Trap

    AI native infrastructure is no longer optional; it is the foundation enterprises need to scale AI reliably, securely, and cost effectively. In this episode, Independent AI Strategist Ritu Jyoti sits down with Lavanya Shukla, Senior Director of AI at CoreWeave, to expose the AI ops black hole and explain why GPUs alone will never get AI models safely into production. You will learn how hidden complexity, fragmented tooling, and legacy AIOps quietly drain AI ROI and stall even the most ambitious AI roadmaps. Together, Ritu and Lavanya unpack why general purpose clouds create an operational trap for modern AI workloads. They break down how probabilistic models, multi cloud deployments, and disconnected observability tools increase cognitive load, slow experimentation, and introduce serious business and compliance risk. Drawing on real world experience with large scale AI deployments, they outline how AI native cloud architecture and model aware observability restore trust, speed, and control across the entire AI lifecycle. In this episode, you will learn: Why the AI ops black hole is the real reason AI initiatives fail at scale How general purpose cloud infrastructure creates hidden time and complexity costs Why traditional AIOps breaks down for probabilistic and generative AI systems What model aware observability looks like and why it is non negotiable How AI native cloud architecture reduces integration debt and developer burnout The concrete steps leaders can take to move from fragile prototypes to production ready AI Do not risk stalled deployments, burned out engineers, and AI systems you cannot trust. Learn how to escape the AI ops black hole and build AI platforms that scale with confidence, clarity, and measurable business impact.

    22 min
  5. 12/30/2025

    Beyond GPUs: What True AI-Native Infrastructure Really Means

    AI-native infrastructure is no longer optional; it is the foundation every modern enterprise needs to scale AI reliably and cost effectively. In this episode, Independent AI Strategist Ritu Jyoti sits down with Jacob Feldman, Lead Solutions Architect at CoreWeave, to break down what true AI-native infrastructure really means and why GPUs alone will not get your models into production. You will learn how the right architecture can eliminate bottlenecks, reduce training time, and unlock the performance your AI teams have been missing. Together, Ritu and Jacob unpack the full AI stack: networking, storage, orchestration, security, and observability, and explain how each layer impacts speed, cost, and long term ROI. They share real-world insights from working with leading CIOs, CTOs, and Heads of AI, giving you a clear blueprint for moving from pilot experiments to scalable AI deployment. In this episode, you will learn: Why general purpose cloud slows AI teams down How InfiniBand, bare metal compute, and AI optimized storage transform performance What AI-native actually means across the full lifecycle (training to inference to continuous refinement) The operational pitfalls that stall enterprise AI and how to avoid them How to build for reliability, scale, and predictable cost in every AI workload Do not risk stalled pilots, rising GPU costs, and fragile architectures. Learn how to build AI systems that truly scale and give your teams the infrastructure advantage they need now.

    32 min

About

Breakthroughs stall when leaders are forced to build the future on foundations from another era. Modern AI demands new thinking, tooling and decision patterns, yet many executives feel trapped by outdated playbooks. AI Cloud Essentials clears that bottleneck. Hosted by Independent AI Value Strategist Ritu Jyoti, the show delivers practical guidance for leaders navigating trillion-parameter models, real-time adaptation and fast-moving AI ecosystems. Each episode offers clear frameworks to help teams innovate faster, scale smarter and reduce friction without jargon or recycled thinking.

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